PH plays a central role in many biological events. To explore the underlying molecular mechanisms, it is of importance to determine pKa values of ionizable residues in proteins. In this work, DeepKa, a deep learning-based protein pKa predictor, was employed to create the pKa database DeepKa DB (http://computbiophys.com/DeepKa/database) that contains pKa data of over 30 million residues in about 200 thousand soluble proteins. The database was updated to the existing DeepKa web server from which users can obtain the data of interest freely. In addition to the data presentation, case studies were set up to demonstrate how pKa's extracted from the database could be applied to the investigation of pH-dependent processes in proteins.